Pandas Profiling Report

Dataset statistics

Number of variables	18
Number of observations	4600
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	647.0 KiB
Average record size in memory	144.0 B

Variable types

Categorical	8
Numeric	10

Alerts

`country` has constant value "USA"	Constant
`date` has a high cardinality: 70 distinct values	High cardinality
`street` has a high cardinality: 4525 distinct values	High cardinality
`statezip` has a high cardinality: 77 distinct values	High cardinality
`price` is highly correlated with `sqft_living` and 1 other fields	High correlation
`bedrooms` is highly correlated with `bathrooms` and 1 other fields	High correlation
`bathrooms` is highly correlated with `bedrooms` and 4 other fields	High correlation
`sqft_living` is highly correlated with `price` and 3 other fields	High correlation
`sqft_lot` is highly correlated with `country`	High correlation
`floors` is highly correlated with `yr_built` and 1 other fields	High correlation
`sqft_above` is highly correlated with `price` and 5 other fields	High correlation
`sqft_basement` is highly correlated with `bathrooms` and 2 other fields	High correlation
`yr_built` is highly correlated with `bathrooms` and 5 other fields	High correlation
`yr_renovated` is highly correlated with `yr_built`	High correlation
`date` is highly correlated with `country`	High correlation
`waterfront` is highly correlated with `country`	High correlation
`view` is highly correlated with `country`	High correlation
`condition` is highly correlated with `yr_built`	High correlation
`city` is highly correlated with `yr_built` and 1 other fields	High correlation
`statezip` is highly correlated with `floors` and 3 other fields	High correlation
`country` is highly correlated with `view` and 5 other fields	High correlation
`price` is highly skewed (γ1 = 24.79093256)	Skewed
`street` is uniformly distributed	Uniform
`price` has 49 (1.1%) zeros	Zeros
`sqft_basement` has 2745 (59.7%) zeros	Zeros
`yr_renovated` has 2735 (59.5%) zeros	Zeros

Reproduction

Analysis started	2022-11-05 12:56:39.557043
Analysis finished	2022-11-05 12:56:51.513058
Duration	11.96 seconds
Software version	pandas-profiling v3.4.0
Download configuration	config.json

date
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct	70
Distinct (%)	1.5%
Missing	0
Missing (%)	0.0%
Memory size	36.1 KiB

2014-06-23 00:00:00	142
2014-06-25 00:00:00	131
2014-06-26 00:00:00	131
2014-07-08 00:00:00	127
2014-07-09 00:00:00	121
Other values (65)	3948

Length

Max length	19
Median length	19
Mean length	19
Min length	19

Characters and Unicode

Total characters	87400
Distinct characters	13
Distinct categories	4 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	2014-05-02 00:00:00
2nd row	2014-05-02 00:00:00
3rd row	2014-05-02 00:00:00
4th row	2014-05-02 00:00:00
5th row	2014-05-02 00:00:00

Common Values

Value	Count	Frequency (%)
2014-06-23 00:00:00	142	3.1%
2014-06-25 00:00:00	131	2.8%
2014-06-26 00:00:00	131	2.8%
2014-07-08 00:00:00	127	2.8%
2014-07-09 00:00:00	121	2.6%
2014-06-24 00:00:00	120	2.6%
2014-07-01 00:00:00	116	2.5%
2014-05-20 00:00:00	116	2.5%
2014-06-17 00:00:00	113	2.5%
2014-05-28 00:00:00	111	2.4%
Other values (60)	3372	73.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
00:00:00	4600	50.0%
2014-06-23	142	1.5%
2014-06-25	131	1.4%
2014-06-26	131	1.4%
2014-07-08	127	1.4%
2014-07-09	121	1.3%
2014-06-24	120	1.3%
2014-07-01	116	1.3%
2014-05-20	116	1.3%
2014-06-17	113	1.2%
Other values (61)	3483	37.9%

Most occurring characters

Value	Count	Frequency (%)
0	38976	44.6%
-	9200	10.5%
:	9200	10.5%
2	6569	7.5%
1	6236	7.1%
4	4927	5.6%
	4600	5.3%
6	2641	3.0%
5	2176	2.5%
7	1143	1.3%
Other values (3)	1732	2.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	64400	73.7%
Dash Punctuation	9200	10.5%
Other Punctuation	9200	10.5%
Space Separator	4600	5.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	38976	60.5%
2	6569	10.2%
1	6236	9.7%
4	4927	7.7%
6	2641	4.1%
5	2176	3.4%
7	1143	1.8%
3	721	1.1%
9	563	0.9%
8	448	0.7%

Dash Punctuation

Value	Count	Frequency (%)
-	9200	100.0%

Other Punctuation

Value	Count	Frequency (%)
:	9200	100.0%

Space Separator

Value	Count	Frequency (%)
	4600	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	87400	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	38976	44.6%
-	9200	10.5%
:	9200	10.5%
2	6569	7.5%
1	6236	7.1%
4	4927	5.6%
	4600	5.3%
6	2641	3.0%
5	2176	2.5%
7	1143	1.3%
Other values (3)	1732	2.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	87400	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	38976	44.6%
-	9200	10.5%
:	9200	10.5%
2	6569	7.5%
1	6236	7.1%
4	4927	5.6%
	4600	5.3%
6	2641	3.0%
5	2176	2.5%
7	1143	1.3%
Other values (3)	1732	2.0%

price
Real number (ℝ_≥0)

HIGH CORRELATION
SKEWED
ZEROS

Distinct	1741
Distinct (%)	37.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	551962.9885

Minimum	0
Maximum	26590000
Zeros	49
Zeros (%)	1.1%
Negative	0
Negative (%)	0.0%
Memory size	36.1 KiB

Quantile statistics

Minimum	0
5-th percentile	200000
Q1	322875
median	460943.4615
Q3	654962.5
95-th percentile	1184050
Maximum	26590000
Range	26590000
Interquartile range (IQR)	332087.5

Descriptive statistics

Standard deviation	563834.7025
Coefficient of variation (CV)	1.021508171
Kurtosis	1044.352151
Mean	551962.9885
Median Absolute Deviation (MAD)	157500
Skewness	24.79093256
Sum	2539029747
Variance	3.179095718 × 10¹¹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	49	1.1%
300000	42	0.9%
400000	31	0.7%
440000	29	0.6%
450000	29	0.6%
600000	29	0.6%
350000	28	0.6%
250000	27	0.6%
435000	27	0.6%
415000	27	0.6%
Other values (1731)	4282	93.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	49	1.1%
7800	1	< 0.1%
80000	1	< 0.1%
83000	1	< 0.1%
83300	2	< 0.1%
84350	1	< 0.1%
87500	1	< 0.1%
90000	2	< 0.1%
100000	4	0.1%
102500	1	< 0.1%

Value	Count	Frequency (%)
26590000	1	< 0.1%
12899000	1	< 0.1%
7062500	1	< 0.1%
4668000	1	< 0.1%
4489000	1	< 0.1%
3800000	1	< 0.1%
3710000	1	< 0.1%
3200000	1	< 0.1%
3100000	1	< 0.1%
3000000	1	< 0.1%

bedrooms
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	10
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.400869565

Minimum	0
Maximum	9
Zeros	2
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	36.1 KiB

Quantile statistics

Minimum	0
5-th percentile	2
Q1	3
median	3
Q3	4
95-th percentile	5
Maximum	9
Range	9
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.9088481155
Coefficient of variation (CV)	0.2672399215
Kurtosis	1.235377429
Mean	3.400869565
Median Absolute Deviation (MAD)	1
Skewness	0.456446633
Sum	15644
Variance	0.8260048971
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
3	2032	44.2%
4	1531	33.3%
2	566	12.3%
5	353	7.7%
6	61	1.3%
1	38	0.8%
7	14	0.3%
8	2	< 0.1%
0	2	< 0.1%
9	1	< 0.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	2	< 0.1%
1	38	0.8%
2	566	12.3%
3	2032	44.2%
4	1531	33.3%
5	353	7.7%
6	61	1.3%
7	14	0.3%
8	2	< 0.1%
9	1	< 0.1%

Value	Count	Frequency (%)
9	1	< 0.1%
8	2	< 0.1%
7	14	0.3%
6	61	1.3%
5	353	7.7%
4	1531	33.3%
3	2032	44.2%
2	566	12.3%
1	38	0.8%
0	2	< 0.1%

bathrooms
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	26
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.160815217

Minimum	0
Maximum	8
Zeros	2
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	36.1 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	1.75
median	2.25
Q3	2.5
95-th percentile	3.5
Maximum	8
Range	8
Interquartile range (IQR)	0.75

Descriptive statistics

Standard deviation	0.7837810747
Coefficient of variation (CV)	0.3627247107
Kurtosis	1.86590471
Mean	2.160815217
Median Absolute Deviation (MAD)	0.5
Skewness	0.6160327234
Sum	9939.75
Variance	0.614312773
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=26)

Value	Count	Frequency (%)
2.5	1189	25.8%
1	743	16.2%
1.75	629	13.7%
2	427	9.3%
2.25	419	9.1%
1.5	291	6.3%
2.75	276	6.0%
3	167	3.6%
3.5	162	3.5%
3.25	136	3.0%
Other values (16)	161	3.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	2	< 0.1%
0.75	17	0.4%
1	743	16.2%
1.25	3	0.1%
1.5	291	6.3%
1.75	629	13.7%
2	427	9.3%
2.25	419	9.1%
2.5	1189	25.8%
2.75	276	6.0%

Value	Count	Frequency (%)
8	1	< 0.1%
6.75	1	< 0.1%
6.5	1	< 0.1%
6.25	2	< 0.1%
5.75	1	< 0.1%
5.5	4	0.1%
5.25	4	0.1%
5	6	0.1%
4.75	7	0.2%
4.5	29	0.6%

sqft_living
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	566
Distinct (%)	12.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2139.346957

Minimum	370
Maximum	13540
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	36.1 KiB

Quantile statistics

Minimum	370
5-th percentile	950
Q1	1460
median	1980
Q3	2620
95-th percentile	3870
Maximum	13540
Range	13170
Interquartile range (IQR)	1160

Descriptive statistics

Standard deviation	963.2069158
Coefficient of variation (CV)	0.4502340833
Kurtosis	8.2916826
Mean	2139.346957
Median Absolute Deviation (MAD)	570
Skewness	1.723513271
Sum	9840996
Variance	927767.5626
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1940	32	0.7%
1720	32	0.7%
1660	31	0.7%
1840	31	0.7%
2000	30	0.7%
1410	29	0.6%
1200	28	0.6%
1480	28	0.6%
1700	27	0.6%
1490	27	0.6%
Other values (556)	4305	93.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
370	1	< 0.1%
380	1	< 0.1%
420	1	< 0.1%
430	1	< 0.1%
490	1	< 0.1%
520	1	< 0.1%
550	1	< 0.1%
560	1	< 0.1%
580	1	< 0.1%
590	2	< 0.1%

Value	Count	Frequency (%)
13540	1	< 0.1%
10040	1	< 0.1%
9640	1	< 0.1%
8670	1	< 0.1%
8020	1	< 0.1%
7320	1	< 0.1%
7270	1	< 0.1%
7050	1	< 0.1%
6980	1	< 0.1%
6900	1	< 0.1%

sqft_lot
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	3113
Distinct (%)	67.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	14852.51609

Minimum	638
Maximum	1074218
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	36.1 KiB

Quantile statistics

Minimum	638
5-th percentile	1690.8
Q1	5000.75
median	7683
Q3	11001.25
95-th percentile	43560
Maximum	1074218
Range	1073580
Interquartile range (IQR)	6000.5

Descriptive statistics

Standard deviation	35884.43614
Coefficient of variation (CV)	2.416050987
Kurtosis	219.8729874
Mean	14852.51609
Median Absolute Deviation (MAD)	2772
Skewness	11.30713875
Sum	68321574
Variance	1287692757
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
5000	80	1.7%
6000	65	1.4%
4000	54	1.2%
7200	50	1.1%
4800	29	0.6%
4500	25	0.5%
9600	25	0.5%
3000	23	0.5%
5500	23	0.5%
7500	23	0.5%
Other values (3103)	4203	91.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
638	1	< 0.1%
681	1	< 0.1%
704	1	< 0.1%
746	1	< 0.1%
747	1	< 0.1%
750	1	< 0.1%
779	1	< 0.1%
833	1	< 0.1%
835	1	< 0.1%
844	2	< 0.1%

Value	Count	Frequency (%)
1074218	1	< 0.1%
641203	1	< 0.1%
478288	1	< 0.1%
435600	2	< 0.1%
423838	1	< 0.1%
389126	1	< 0.1%
327135	1	< 0.1%
307752	1	< 0.1%
306848	1	< 0.1%
284011	1	< 0.1%

floors
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	6
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.512065217

Minimum	1
Maximum	3.5
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	36.1 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	1.5
Q3	2
95-th percentile	2
Maximum	3.5
Range	2.5
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.5382883773
Coefficient of variation (CV)	0.3559954763
Kurtosis	-0.5388519795
Mean	1.512065217
Median Absolute Deviation (MAD)	0.5
Skewness	0.5514406463
Sum	6955.5
Variance	0.2897543771
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
1	2174	47.3%
2	1811	39.4%
1.5	444	9.7%
3	128	2.8%
2.5	41	0.9%
3.5	2	< 0.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	2174	47.3%
1.5	444	9.7%
2	1811	39.4%
2.5	41	0.9%
3	128	2.8%
3.5	2	< 0.1%

Value	Count	Frequency (%)
3.5	2	< 0.1%
3	128	2.8%
2.5	41	0.9%
2	1811	39.4%
1.5	444	9.7%
1	2174	47.3%

waterfront
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	36.1 KiB

0	4567
1	33

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	4600
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	4567	99.3%
1	33	0.7%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	4567	99.3%
1	33	0.7%

Most occurring characters

Value	Count	Frequency (%)
0	4567	99.3%
1	33	0.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4600	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4567	99.3%
1	33	0.7%

Most occurring scripts

Value	Count	Frequency (%)
Common	4600	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4567	99.3%
1	33	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4600	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4567	99.3%
1	33	0.7%

view
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	36.1 KiB

0	4140
2	205
3	116
4	70
1	69

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	4600
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	4
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	4140	90.0%
2	205	4.5%
3	116	2.5%
4	70	1.5%
1	69	1.5%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	4140	90.0%
2	205	4.5%
3	116	2.5%
4	70	1.5%
1	69	1.5%

Most occurring characters

Value	Count	Frequency (%)
0	4140	90.0%
2	205	4.5%
3	116	2.5%
4	70	1.5%
1	69	1.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4600	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4140	90.0%
2	205	4.5%
3	116	2.5%
4	70	1.5%
1	69	1.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	4600	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4140	90.0%
2	205	4.5%
3	116	2.5%
4	70	1.5%
1	69	1.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4600	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4140	90.0%
2	205	4.5%
3	116	2.5%
4	70	1.5%
1	69	1.5%

condition
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	36.1 KiB

3	2875
4	1252
5	435
2	32
1	6

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	4600
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	3
2nd row	5
3rd row	4
4th row	4
5th row	4

Common Values

Value	Count	Frequency (%)
3	2875	62.5%
4	1252	27.2%
5	435	9.5%
2	32	0.7%
1	6	0.1%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
3	2875	62.5%
4	1252	27.2%
5	435	9.5%
2	32	0.7%
1	6	0.1%

Most occurring characters

Value	Count	Frequency (%)
3	2875	62.5%
4	1252	27.2%
5	435	9.5%
2	32	0.7%
1	6	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4600	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
3	2875	62.5%
4	1252	27.2%
5	435	9.5%
2	32	0.7%
1	6	0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	4600	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
3	2875	62.5%
4	1252	27.2%
5	435	9.5%
2	32	0.7%
1	6	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4600	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
3	2875	62.5%
4	1252	27.2%
5	435	9.5%
2	32	0.7%
1	6	0.1%

sqft_above
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	511
Distinct (%)	11.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1827.265435

Minimum	370
Maximum	9410
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	36.1 KiB

Quantile statistics

Minimum	370
5-th percentile	860
Q1	1190
median	1590
Q3	2300
95-th percentile	3440
Maximum	9410
Range	9040
Interquartile range (IQR)	1110

Descriptive statistics

Standard deviation	862.168977
Coefficient of variation (CV)	0.4718356515
Kurtosis	4.070138265
Mean	1827.265435
Median Absolute Deviation (MAD)	490
Skewness	1.494210748
Sum	8405421
Variance	743335.3448
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1200	47	1.0%
1010	47	1.0%
1300	45	1.0%
1140	44	1.0%
1320	43	0.9%
1150	42	0.9%
1090	40	0.9%
1180	40	0.9%
1400	38	0.8%
1050	37	0.8%
Other values (501)	4177	90.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
370	1	< 0.1%
380	1	< 0.1%
420	1	< 0.1%
430	1	< 0.1%
490	1	< 0.1%
520	1	< 0.1%
550	3	0.1%
560	1	< 0.1%
580	1	< 0.1%
590	2	< 0.1%

Value	Count	Frequency (%)
9410	1	< 0.1%
8020	1	< 0.1%
7680	1	< 0.1%
7320	1	< 0.1%
6640	1	< 0.1%
6430	1	< 0.1%
6420	1	< 0.1%
6120	1	< 0.1%
6070	1	< 0.1%
6050	1	< 0.1%

sqft_basement
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	207
Distinct (%)	4.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	312.0815217

Minimum	0
Maximum	4820
Zeros	2745
Zeros (%)	59.7%
Negative	0
Negative (%)	0.0%
Memory size	36.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	610
95-th percentile	1210
Maximum	4820
Range	4820
Interquartile range (IQR)	610

Descriptive statistics

Standard deviation	464.1372281
Coefficient of variation (CV)	1.487230726
Kurtosis	4.082380024
Mean	312.0815217
Median Absolute Deviation (MAD)	0
Skewness	1.642732192
Sum	1435575
Variance	215423.3665
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	2745	59.7%
500	53	1.2%
600	45	1.0%
800	43	0.9%
900	41	0.9%
700	38	0.8%
1000	33	0.7%
400	33	0.7%
550	27	0.6%
750	26	0.6%
Other values (197)	1516	33.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	2745	59.7%
20	1	< 0.1%
50	1	< 0.1%
60	2	< 0.1%
65	1	< 0.1%
70	1	< 0.1%
80	3	0.1%
90	2	< 0.1%
100	14	0.3%
110	2	< 0.1%

Value	Count	Frequency (%)
4820	1	< 0.1%
4130	1	< 0.1%
2850	1	< 0.1%
2730	1	< 0.1%
2550	2	< 0.1%
2360	1	< 0.1%
2330	1	< 0.1%
2300	1	< 0.1%
2200	1	< 0.1%
2180	1	< 0.1%

yr_built
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	115
Distinct (%)	2.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1970.786304

Minimum	1900
Maximum	2014
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	36.1 KiB

Quantile statistics

Minimum	1900
5-th percentile	1913
Q1	1951
median	1976
Q3	1997
95-th percentile	2009
Maximum	2014
Range	114
Interquartile range (IQR)	46

Descriptive statistics

Standard deviation	29.73184839
Coefficient of variation (CV)	0.0150862873
Kurtosis	-0.6700759004
Mean	1970.786304
Median Absolute Deviation (MAD)	23
Skewness	-0.50215519
Sum	9065617
Variance	883.9828087
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2006	111	2.4%
2005	104	2.3%
2007	93	2.0%
2004	92	2.0%
1978	90	2.0%
2003	89	1.9%
2008	89	1.9%
1967	82	1.8%
1977	80	1.7%
2014	78	1.7%
Other values (105)	3692	80.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1900	22	0.5%
1901	9	0.2%
1902	10	0.2%
1903	10	0.2%
1904	9	0.2%
1905	19	0.4%
1906	27	0.6%
1907	12	0.3%
1908	19	0.4%
1909	22	0.5%

Value	Count	Frequency (%)
2014	78	1.7%
2013	57	1.2%
2012	33	0.7%
2011	24	0.5%
2010	28	0.6%
2009	50	1.1%
2008	89	1.9%
2007	93	2.0%
2006	111	2.4%
2005	104	2.3%

yr_renovated
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	60
Distinct (%)	1.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	808.6082609

Minimum	0
Maximum	2014
Zeros	2735
Zeros (%)	59.5%
Negative	0
Negative (%)	0.0%
Memory size	36.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	1999
95-th percentile	2011
Maximum	2014
Range	2014
Interquartile range (IQR)	1999

Descriptive statistics

Standard deviation	979.4145364
Coefficient of variation (CV)	1.211234888
Kurtosis	-1.851110913
Mean	808.6082609
Median Absolute Deviation (MAD)	0
Skewness	0.3859187009
Sum	3719598
Variance	959252.8341
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	2735	59.5%
2000	170	3.7%
2003	151	3.3%
2009	109	2.4%
2001	109	2.4%
2005	95	2.1%
2004	77	1.7%
2014	72	1.6%
2006	68	1.5%
2013	61	1.3%
Other values (50)	953	20.7%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	2735	59.5%
1912	33	0.7%
1913	1	< 0.1%
1923	57	1.2%
1934	6	0.1%
1945	7	0.2%
1948	1	< 0.1%
1953	1	< 0.1%
1954	8	0.2%
1955	2	< 0.1%

Value	Count	Frequency (%)
2014	72	1.6%
2013	61	1.3%
2012	45	1.0%
2011	54	1.2%
2010	30	0.7%
2009	109	2.4%
2008	45	1.0%
2007	7	0.2%
2006	68	1.5%
2005	95	2.1%

street
Categorical

HIGH CARDINALITY
UNIFORM

Distinct	4525
Distinct (%)	98.4%
Missing	0
Missing (%)	0.0%
Memory size	36.1 KiB

2520 Mulberry Walk NE	4
2500 Mulberry Walk NE	3
9413 34th Ave SW	2
6008 8th Ave NE	2
11034 NE 26th Pl	2
Other values (4520)	4587

Length

Max length	46
Median length	40
Mean length	17.01826087
Min length	8

Characters and Unicode

Total characters	78284
Distinct characters	62
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4453 ?
Unique (%)	96.8%

Sample

1st row	18810 Densmore Ave N
2nd row	709 W Blaine St
3rd row	26206-26214 143rd Ave SE
4th row	857 170th Pl NE
5th row	9105 170th Ave NE

Common Values

Value	Count	Frequency (%)
2520 Mulberry Walk NE	4	0.1%
2500 Mulberry Walk NE	3	0.1%
9413 34th Ave SW	2	< 0.1%
6008 8th Ave NE	2	< 0.1%
11034 NE 26th Pl	2	< 0.1%
14583 NE 58th St	2	< 0.1%
8430 8th Ave SW	2	< 0.1%
5010 Greenwood Ave N	2	< 0.1%
22840 SE 269th St	2	< 0.1%
3510 S Holly St	2	< 0.1%
Other values (4515)	4577	99.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
ave	1940	10.5%
ne	1358	7.4%
se	1180	6.4%
st	1171	6.3%
pl	807	4.4%
s	562	3.0%
sw	513	2.8%
n	292	1.6%
nw	288	1.6%
ct	173	0.9%
Other values (4805)	10157	55.1%

Most occurring characters

Value	Count	Frequency (%)
	13841	17.7%
1	5952	7.6%
t	4628	5.9%
2	4618	5.9%
S	3522	4.5%
0	3119	4.0%
3	3090	3.9%
e	2891	3.7%
h	2787	3.6%
4	2775	3.5%
Other values (52)	31061	39.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	29557	37.8%
Lowercase Letter	20844	26.6%
Space Separator	13841	17.7%
Uppercase Letter	13697	17.5%
Dash Punctuation	343	0.4%
Other Punctuation	2	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
t	4628	22.2%
e	2891	13.9%
h	2787	13.4%
v	2044	9.8%
l	1311	6.3%
r	1115	5.3%
n	1066	5.1%
d	1000	4.8%
a	907	4.4%
s	589	2.8%
Other values (15)	2506	12.0%

Uppercase Letter

Value	Count	Frequency (%)
S	3522	25.7%
E	2718	19.8%
A	2018	14.7%
N	1966	14.4%
W	1183	8.6%
P	895	6.5%
C	283	2.1%
D	184	1.3%
L	150	1.1%
M	148	1.1%
Other values (14)	630	4.6%

Decimal Number

Value	Count	Frequency (%)
1	5952	20.1%
2	4618	15.6%
0	3119	10.6%
3	3090	10.5%
4	2775	9.4%
5	2409	8.2%
6	2060	7.0%
7	1928	6.5%
8	1849	6.3%
9	1757	5.9%

Space Separator

Value	Count	Frequency (%)
	13841	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	343	100.0%

Other Punctuation

Value	Count	Frequency (%)
/	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	43743	55.9%
Latin	34541	44.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
t	4628	13.4%
S	3522	10.2%
e	2891	8.4%
h	2787	8.1%
E	2718	7.9%
v	2044	5.9%
A	2018	5.8%
N	1966	5.7%
l	1311	3.8%
W	1183	3.4%
Other values (39)	9473	27.4%

Common

Value	Count	Frequency (%)
	13841	31.6%
1	5952	13.6%
2	4618	10.6%
0	3119	7.1%
3	3090	7.1%
4	2775	6.3%
5	2409	5.5%
6	2060	4.7%
7	1928	4.4%
8	1849	4.2%
Other values (3)	2102	4.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	78284	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	13841	17.7%
1	5952	7.6%
t	4628	5.9%
2	4618	5.9%
S	3522	4.5%
0	3119	4.0%
3	3090	3.9%
e	2891	3.7%
h	2787	3.6%
4	2775	3.5%
Other values (52)	31061	39.7%

city
Categorical

HIGH CORRELATION

Distinct	44
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	36.1 KiB

Seattle	1573
Renton	293
Bellevue	286
Redmond	235
Issaquah	187
Other values (39)	2026

Length

Max length	19
Median length	18
Mean length	7.753913043
Min length	4

Characters and Unicode

Total characters	35668
Distinct characters	45
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	0.1%

Sample

1st row	Shoreline
2nd row	Seattle
3rd row	Kent
4th row	Bellevue
5th row	Redmond

Common Values

Value	Count	Frequency (%)
Seattle	1573	34.2%
Renton	293	6.4%
Bellevue	286	6.2%
Redmond	235	5.1%
Issaquah	187	4.1%
Kirkland	187	4.1%
Kent	185	4.0%
Auburn	176	3.8%
Sammamish	175	3.8%
Federal Way	148	3.2%
Other values (34)	1155	25.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
seattle	1573	30.4%
renton	293	5.7%
bellevue	286	5.5%
redmond	235	4.5%
issaquah	187	3.6%
kirkland	187	3.6%
kent	185	3.6%
auburn	176	3.4%
sammamish	175	3.4%
federal	148	2.9%
Other values (47)	1722	33.3%

Most occurring characters

Value	Count	Frequency (%)
e	6423	18.0%
t	3861	10.8%
l	3602	10.1%
a	3573	10.0%
n	2261	6.3%
S	1975	5.5%
o	1382	3.9%
r	1137	3.2%
d	1113	3.1%
i	1079	3.0%
Other values (35)	9262	26.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	29903	83.8%
Uppercase Letter	5197	14.6%
Space Separator	567	1.6%
Dash Punctuation	1	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	6423	21.5%
t	3861	12.9%
l	3602	12.0%
a	3573	11.9%
n	2261	7.6%
o	1382	4.6%
r	1137	3.8%
d	1113	3.7%
i	1079	3.6%
u	1071	3.6%
Other values (14)	4401	14.7%

Uppercase Letter

Value	Count	Frequency (%)
S	1975	38.0%
R	535	10.3%
B	453	8.7%
K	438	8.4%
I	274	5.3%
W	263	5.1%
M	253	4.9%
F	196	3.8%
A	182	3.5%
V	126	2.4%
Other values (9)	502	9.7%

Space Separator

Value	Count	Frequency (%)
	567	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	35100	98.4%
Common	568	1.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	6423	18.3%
t	3861	11.0%
l	3602	10.3%
a	3573	10.2%
n	2261	6.4%
S	1975	5.6%
o	1382	3.9%
r	1137	3.2%
d	1113	3.2%
i	1079	3.1%
Other values (33)	8694	24.8%

Common

Value	Count	Frequency (%)
	567	99.8%
-	1	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	35668	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	6423	18.0%
t	3861	10.8%
l	3602	10.1%
a	3573	10.0%
n	2261	6.3%
S	1975	5.5%
o	1382	3.9%
r	1137	3.2%
d	1113	3.1%
i	1079	3.0%
Other values (35)	9262	26.0%

statezip
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct	77
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	36.1 KiB

WA 98103	148
WA 98052	135
WA 98117	132
WA 98115	130
WA 98006	110
Other values (72)	3945

Length

Max length	8
Median length	8
Mean length	8
Min length	8

Characters and Unicode

Total characters	36800
Distinct characters	13
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	WA 98133
2nd row	WA 98119
3rd row	WA 98042
4th row	WA 98008
5th row	WA 98052

Common Values

Value	Count	Frequency (%)
WA 98103	148	3.2%
WA 98052	135	2.9%
WA 98117	132	2.9%
WA 98115	130	2.8%
WA 98006	110	2.4%
WA 98059	106	2.3%
WA 98042	100	2.2%
WA 98034	99	2.2%
WA 98053	98	2.1%
WA 98074	98	2.1%
Other values (67)	3444	74.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
wa	4600	50.0%
98103	148	1.6%
98052	135	1.5%
98117	132	1.4%
98115	130	1.4%
98006	110	1.2%
98059	106	1.2%
98042	100	1.1%
98034	99	1.1%
98074	98	1.1%
Other values (68)	3542	38.5%

Most occurring characters

Value	Count	Frequency (%)
8	5274	14.3%
9	5201	14.1%
W	4600	12.5%
A	4600	12.5%
	4600	12.5%
0	3695	10.0%
1	2741	7.4%
5	1275	3.5%
2	1244	3.4%
3	1146	3.1%
Other values (3)	2424	6.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	23000	62.5%
Uppercase Letter	9200	25.0%
Space Separator	4600	12.5%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
8	5274	22.9%
9	5201	22.6%
0	3695	16.1%
1	2741	11.9%
5	1275	5.5%
2	1244	5.4%
3	1146	5.0%
7	876	3.8%
4	778	3.4%
6	770	3.3%

Uppercase Letter

Value	Count	Frequency (%)
W	4600	50.0%
A	4600	50.0%

Space Separator

Value	Count	Frequency (%)
	4600	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	27600	75.0%
Latin	9200	25.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
8	5274	19.1%
9	5201	18.8%
	4600	16.7%
0	3695	13.4%
1	2741	9.9%
5	1275	4.6%
2	1244	4.5%
3	1146	4.2%
7	876	3.2%
4	778	2.8%

Latin

Value	Count	Frequency (%)
W	4600	50.0%
A	4600	50.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	36800	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
8	5274	14.3%
9	5201	14.1%
W	4600	12.5%
A	4600	12.5%
	4600	12.5%
0	3695	10.0%
1	2741	7.4%
5	1275	3.5%
2	1244	3.4%
3	1146	3.1%
Other values (3)	2424	6.6%

country
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	36.1 KiB

USA	4600

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	13800
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	USA
2nd row	USA
3rd row	USA
4th row	USA
5th row	USA

Common Values

Value	Count	Frequency (%)
USA	4600	100.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
usa	4600	100.0%

Most occurring characters

Value	Count	Frequency (%)
U	4600	33.3%
S	4600	33.3%
A	4600	33.3%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	13800	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
U	4600	33.3%
S	4600	33.3%
A	4600	33.3%

Most occurring scripts

Value	Count	Frequency (%)
Latin	13800	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
U	4600	33.3%
S	4600	33.3%
A	4600	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	13800	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
U	4600	33.3%
S	4600	33.3%
A	4600	33.3%

Auto

The auto setting is an easily interpretable pairwise column metric of the following mapping: vartype-vartype : method, categorical-categorical : Cramer's V, numerical-categorical : Cramer's V (using a discretized numerical column), numerical-numerical : Spearman's ρ. This configuration uses the best suitable for each pair of columns.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	date	price	bedrooms	bathrooms	sqft_living	sqft_lot	floors	view	condition	sqft_above	sqft_basement	yr_built	yr_renovated	street	city	statezip	country
0	2014-05-02 00:00:00	313000.0	3.0	1.50	1340	7912	1.5	0	3	1340	0	1955	2005	18810 Densmore Ave N	Shoreline	WA 98133	USA
1	2014-05-02 00:00:00	2384000.0	5.0	2.50	3650	9050	2.0	4	5	3370	280	1921	0	709 W Blaine St	Seattle	WA 98119	USA
2	2014-05-02 00:00:00	342000.0	3.0	2.00	1930	11947	1.0	0	4	1930	0	1966	0	26206-26214 143rd Ave SE	Kent	WA 98042	USA
3	2014-05-02 00:00:00	420000.0	3.0	2.25	2000	8030	1.0	0	4	1000	1000	1963	0	857 170th Pl NE	Bellevue	WA 98008	USA
4	2014-05-02 00:00:00	550000.0	4.0	2.50	1940	10500	1.0	0	4	1140	800	1976	1992	9105 170th Ave NE	Redmond	WA 98052	USA
5	2014-05-02 00:00:00	490000.0	2.0	1.00	880	6380	1.0	0	3	880	0	1938	1994	522 NE 88th St	Seattle	WA 98115	USA
6	2014-05-02 00:00:00	335000.0	2.0	2.00	1350	2560	1.0	0	3	1350	0	1976	0	2616 174th Ave NE	Redmond	WA 98052	USA
7	2014-05-02 00:00:00	482000.0	4.0	2.50	2710	35868	2.0	0	3	2710	0	1989	0	23762 SE 253rd Pl	Maple Valley	WA 98038	USA
8	2014-05-02 00:00:00	452500.0	3.0	2.50	2430	88426	1.0	0	4	1570	860	1985	0	46611-46625 SE 129th St	North Bend	WA 98045	USA
9	2014-05-02 00:00:00	640000.0	4.0	2.00	1520	6200	1.5	0	3	1520	0	1945	2010	6811 55th Ave NE	Seattle	WA 98115	USA

Last rows

	date	price	bedrooms	bathrooms	sqft_living	sqft_lot	floors	condition	sqft_above	sqft_basement	yr_built	yr_renovated	street	city	statezip	country
4590	2014-07-08 00:00:00	380680.555556	4.0	2.50	2620	8331	2.0	3	2620	0	1991	0	13602 SE 186th Pl	Renton	WA 98058	USA
4591	2014-07-08 00:00:00	396166.666667	3.0	1.75	1880	5752	1.0	4	940	940	1945	0	3529 SW Webster St	Seattle	WA 98126	USA
4592	2014-07-08 00:00:00	252980.000000	4.0	2.50	2530	8169	2.0	3	2530	0	1993	0	37654 18th Pl S	Federal Way	WA 98003	USA
4593	2014-07-08 00:00:00	289373.307692	3.0	2.50	2538	4600	2.0	3	2538	0	2013	1923	5703 Charlotte Ave SE	Auburn	WA 98092	USA
4594	2014-07-09 00:00:00	210614.285714	3.0	2.50	1610	7223	2.0	3	1610	0	1994	0	26306 127th Ave SE	Kent	WA 98030	USA
4595	2014-07-09 00:00:00	308166.666667	3.0	1.75	1510	6360	1.0	4	1510	0	1954	1979	501 N 143rd St	Seattle	WA 98133	USA
4596	2014-07-09 00:00:00	534333.333333	3.0	2.50	1460	7573	2.0	3	1460	0	1983	2009	14855 SE 10th Pl	Bellevue	WA 98007	USA
4597	2014-07-09 00:00:00	416904.166667	3.0	2.50	3010	7014	2.0	3	3010	0	2009	0	759 Ilwaco Pl NE	Renton	WA 98059	USA
4598	2014-07-10 00:00:00	203400.000000	4.0	2.00	2090	6630	1.0	3	1070	1020	1974	0	5148 S Creston St	Seattle	WA 98178	USA
4599	2014-07-10 00:00:00	220600.000000	3.0	2.50	1490	8102	2.0	4	1490	0	1990	0	18717 SE 258th St	Covington	WA 98042	USA

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Dash Punctuation

Other Punctuation

Space Separator

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Decimal Number

Space Separator

Dash Punctuation

Other Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter